Assessing the interconnectedness and systemic risk contagion in the Chinese banking network

PurposeIn this paper, the authors use the balance sheet data to investigate the interconnectedness and risk contagion effects in China's banking sector. They firstly study the network structure and centrality of the interbank network. Then, they investigate how and to what extent the credit shock and liquidity shock can lead to the risk propagation in the banking network.Design/methodology/approachReferring to the theoretical framework by Haldane and May (2011), this paper uses the network topology theory to analyze the contagion mechanism of credit shock and liquidity shock. Centrality measures and log-log plot are used to evaluate the interconnectedness of China's banking network.FindingsThe network topology has shown clustering effects of large banks in China's financial network. If the Industrial and Commercial Bank of China (ICBC) is in distress, the credit shock has little impact on the Chinese banking sector. However, the liquidity shock has shown more substantial effects than that of the credit shock. The discount rate and the rollover ratio play significant roles in determining the contagion effects. If the credit shock and liquidity shock coincide, the contagion effects will be amplified.Research limitations/implicationsThe results of this paper reveal the network structure of China's interbank market and the resilience of banking system to the adverse shock. The findings are valuable for regulators to make policies and supervise the systemic important banks.Originality/valueThe balance sheet data of different types of banks are used to construct a bilateral exposure matrix. Based on the matrix, this paper investigates the knock-on effects of credit shock triggered by the debt default in the interbank market, the knock-on effects of liquidity effects, which is featured by “fire sale” of bank assets, and the contagion effects of combined shocks.

Banks’ liquidity management dynamics: evidence from Indonesia

PurposeThis study aims to cover an important yet largely under-explored topic: the dynamic process of bank liquidity management in a vast developing economy by considering pool of funds hypothesis, signaling hypothesis and risk management hypothesis.Design/methodology/approachThe authors apply the dynamic common correlated effect (DCCE) method with an error correction model format to a long panel datasets of 84 Indonesian banks from January 2003 to August 2019, resulting in 16,800 observations.FindingsThe authors obtain convincing evidence of dynamic liquidity management with an error correction mechanism. The time needed to adjust to a liquidity shock ranges from 2.5 to 3.5 months. The empirical results strongly support the pool of funds and signaling hypotheses, whereas risk management motive appears to have secondary importance.Practical implicationsThe regulator should also encourage banks to diversify liquidity management to include interbank money market and off-balance-sheet instruments. The current condition shows that bank liquidity management is strongly correlated with intermediation dynamics and thus is contracyclical. Banks could end up with tight liquidity in a booming economy, which would pose a severe risk to their financial standing.Originality/valueTo authors’ knowledge, this study is the first to analyze bank liquidity management behavior empirically using a panel error correction mechanism. Here, the authors also try to combine a practitioner perspective with a scientific one.

Monetary and Fiscal Policy through a DSGE Lens

This text is designed to bridge the gap between Ph.D. and undergraduate textbooks in Macroeconomics. The text develops a dynamic stochastic general equilibrium model of money using a cash-in-advance constraint and endogenous production as in the real business cycle literature. The costs of inflation and optimal monetary policy, the impact of labor and capital taxes and as well as optimal fiscal policy are covered. Many extensions, including new Keynesian liquidity shock models are developed. Both standard analytic methods, such as Lagrangian methods, and computational methods using Matlab and Python, are developed as we construct quantitative models.

Interbank financing and business cycle in Europe

Purpose The knowledge of the link between interbank financing and business cycle fluctuations is important in assessing the stability and soundness of the banking sector. The purpose of this paper is to investigate the simultaneous relationship between interbank financing and the business cycle with respect to the financial structure of the bank-based and market-based systems in European countries by using bank-level data from 2007 to 2011. Design/methodology/approach The study employs an innovative instrumenting technique with an instrument of the financial structure to address the simultaneous determination of interbank financing and the business cycle. Findings The results suggest that banks establish pro-cyclical interbank borrowing by increasing their interbank position during booms and reducing it during downturns. Bank-based system performs better in redistributing the liquidity in the economy than the market-based system when there are imperfectly correlated liquidity shocks across regions during the 2007–2009 financial crisis. Practical implications The improvement of banks’ liquidity risk management should be aligned with a specific financial system. The macro-prudential supervisor should require banks in the market-based system to disclose their interbank position on the extent of risk exposure during the liquidity shock period to stabilize the EU banking industry. Originality/value This study is the first to provide policy makers with some novel empirical results concerning the linkage among bank liquidity, the macroeconomic condition and financial structure.

The Insurance Value of Trade Credit

The extensive use of trade credit in all manufacturing sectors, despite its high cost, is an apparent puzzle that economists explain in terms of asymmetric information problems affecting financial markets. The financial constraints arising from credit rationing and limited access to stock markets suffice to induce firms to resort to trade credit as a supplemental source of funding. Nonetheless, empirical evidence shows that also large and liquid firms facing no binding financial constraints use substantial amounts of trade credit. We address this issue by modelling the financial policy of a firm that does not face a binding liquidity constraint but the risk of being constrained in the future. We characterise the optimal amount of trade credit held by such a firm, and we show that a positive probability of facing a liquidity constraint leads the firm to fund its inventories with trade credit, even if cheaper sources of funds are available. The rationale is that trade credit provides implicit coverage against liquidity risk. Therefore, the optimal amount of trade credit grows with the expected size of a possible liquidity shock and with the likelihood of its occurrence.